+3 votes
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asked in Estimation by (567 points)
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5 Answers

+3 votes

I would taken a slightly different approach.

Let’s assume the market for driveless cars consists of 2 car groups in year 2020:

– Group 1 – low price driveless cars for carsharing companies .
These cars will have minimum functionalities and their only job is to move people around. Tesla Model 3 costs $35,000 in 2017. This is a car that has self-driving capabilities and some extra features that is not needed for an Uber / Lyft car. E.g. LCD monitor. Let’s assume an Uber / Lyft driver-less car costs $30,000.

Number of Uber / Lyft cars to be needed is estimated as followed:
Let’s say that in the U.S. 10% of Americans have signed up to Uber / Lyft. And they take 5 rides per week with it. Each ride takes 10 minutes. And currently, an average Uber / Lyft car works for 40 hours per week with 75% utilization. This means there are a total of

10% of 330million = 33million car sharing users
33 million users x 5 rides per week x 10 minutes per ride = 1650 million minutes of rides per week

Let’s assume Uber / Lyft will complete 10% of the rides with self-driving cars in year 2020. So, 10% of 1,650 million minutes = 165K million minutes per week of ride sharing will be completed by driver-less cars.

Let’s say that an average self-driving car works for 22 hours per day at 70% utilization. In other words, one self-driving car can complete 22 hours x 70% x 7 days x 60 minutes = 6,600 minutes of ride per week.

Number of cars needed to serve: 165K million minutes / 6,600 minutes = around 250K cars

That means Uber / Lyft will buy a total of 250,000 driverless cars. Total market size for ride-sharing driverless cars will be
250K x $30,000 = $7.5 billion

– Group 2- Personally owned cars.
Let’s say Tesla and Google will launch their self-driving cars by 2020. Tesla currently sells about 50,000 cars per year and is expecting to significantly ramp up production over the next two years. Let’s say Tesla will sell 500,000 of cars in year 2020.
Tesla cars are currently priced at $35K, $70K, $100K, and $120K. Given most of the volume is expected to come from the Model 3, I will assume the average price of a Tesla car to be $40,000 by year 2020. In other words, I expect the total market of Tesla cars to be
500K x $40K = $20 billion

Google has not started making any cars yet so chances are that the number of cars produced by Google will be small by year 2020. Let’s assume it will be 10% of Tesla, meaning the total sales by Google will be $20B x 10% = $2B

Now, let’s calculate total market size of self-driving cars in the U.S. : $7.5B + $20B + $2B = around $30B

Key assumption made: carsharing companies are making their own cars and are not buying from Google and Tesla. If they were buying from Google and Tesla, then we just needed to estimate the volume of cars sold by Google and Tesla. I have also not included the market size of used Tesla cars that will be upgraded to support self-driving.

answered by (567 points)
For group 1, I liked the length and process. Though, it made many challengeable assumptions like 10% of americans use rideshare 5 times a week.
For group 2, the core of the question is to estimate the number of such cars sold (say in US). I don’t thin we can make one big assumption for the core part of the question.
Hey there
Thanks for the feedback. How would you answer it? Feel free to submit your answer.
There is an aspect of new business opportunities with self driving cars: Children pickup/drop, people with disabilities now able to purchase cars; also delivery services like dry cleaning pick ups, grocery- Fresh pick up. Here is how I would estimate the # of new cars needed for these new biz:
US has 300M pop, lets assume 60% of this pop lives in cities where these business will be profitable. For every person living in a city: 20% will use services solutions, 10% will use ti for child pickup drop off, and 1% will be people with disability who will now buy cars:
(60% *300M* 41%) * $20,000/car
Hi bijan
You mentioned uber / lyft will cover 10% if the rides in group 1.. what about cars for the remainder 90%.. are we counting that?
0 votes

What is the market for driverless cars in 2020.

According to a BCG report, partially self driven cars adoption will start shooting up in 2017 and autonomous car usage will reach its peak in the next 2 decades.

Lets just calculate the market for driverless cars in the United states by 2020

Calculations to come up with the cost of a driverless car in 2020:

Cost of model 3 – which will be released soon is 35K.

Lets say that by 2020 – model 3 becomes driverless and Google’s automous vehicle is out as well. With more manufacturers coming in to the market, lets say the price for driverless cars drops to 25K (28% drop in price)

So price of driverless car in 2020 = 25K

Now lets calculate the market size in US:

Total population of US by 2020 = 350M
Total number of households = 350/3 = 117 M approx (120M households)

Lets say 95% of the population has cars = 95% of 120M = 114M households

Current market penetration for Tesla is 0.3% which might go up to 1% with the drastic price reduction for Model 3 and the introduction of new features including autonomous driving by 2020 (which is an aggressive 200+ % jump)
Lets assume that Google has managed to get Tesla’s original spot and has 0.3% penetration
And rest of the vendors have 0.1%

So total penetration of driverless cars (owned by families) is 1.4%

Therefore households containing driverless cars are 1.4% of 114M = 1.6M households

Market value = 1.6M * 25K = 40000000000 = 40B

In addition to households, Uber and Lyft and other rideshare services will also have driverless cars. The policeforce, nnews agencies etc may also start using driverless cars.
We can double our number to assume number of additional driverless cars for commercial/military purposes to arrive at : 80B

answered by (149 points)
0 votes

I like your approach better Bijan! Thanks

answered by (149 points)
0 votes

There are a lot of washers and dryer combos out there and the one that has recently made a name for itself is Xeros – which saves water and detergent.

I would like to take the standard washer and dryer product and try to address some basic pain points that I would like to solve in priority order:

1.What should be my wash/dry cycle?- Having to figure out whether you need a gentle wash cycle, a standard wash cycle or a heavy-duty wash cycle. Similarly – how long should I dry my clothes without damaging them? How am I impacting the life of my clothes by washing/drying them as often as I do?

2. Mixing colored and white clothes – Many of us have done this. We have accidentally added a colored piece of clothing to a load of whites or have not bothered with separating the whites and the colored clothing and gotten a pile of tie-dyed clothes. I would like to figure out a smart way to solve this problem.

3. Noisy sounds to indicate that my washer or dryer is done with its job – Many washer- dryers have noisy alerts at the end of a cycle to indicate that the cycle is complete. I would like to have a quieter and more subtle indicator that the job is done

4. Folding clothes – This is a little bit of a moonshot but its harder to find time to sort, fold and put away clothes as compared to washing and drying them.

5. Moving clothes from the washer to the dryer – One of the other pain points for washer-dryer systems is moving clothes out from the washer and moving them to the dryer. I would like to have a way for clothes to either wash and dry in the same system. Or if its not optimal to design a system to be a washer and a dryer – I would like to build a capability to automatically move the clothes from the washer to the dryer

Problem 1:
a. I would use camera vision to determine the nature of the clothes (silk, cotton, etc) that are being put in to the washer and to understand how dirty they are – and recommend a wash cycle for the clothes.
b. I would have a capability to weigh the load (and use information from #1 to automatically to determine the amount of detergent and water required to wash them.
c. I would also have a container/module to store the detergent from which the right quantity of detergent can be extracted based on on the nature, weight and soiled condition of the clothes.
d. Depending on the outcome of the wash – the user can provide feedback about the wash which would help improve the quality of the wash recommendation going forward.

Customer benefit: That way- you take the guess work out of the process and the machine can help make the decision. The algorithm gets better with customer feedback. You would train the module with manual input – with image recognition, time prediction, detergent and water quantity prediction data

The entire UI can be on the mobile device of the user and can be operated through the washer-dryer mobile app.
Once you load the machine, you dont even need to stand there to set your wash cycle.

Cons – This could be very expensive from a implementation and hardware perspective.

Problem 2: Again, I would use camera vision to determine if there is a colored piece of clothing in the load that might affect the whole load and provide mobile alerts to the user to remove the clothing. Better yet, if we have a eject capability to take out the suspect piece of clothing from the load.

Pros – You can rest assured that the machine will detect any mistakes that humans might have made. You can stop the cycle from your phone in case you/machine are not in a position to take out the colored clothing from the machine.
Cons – While it is fairly easy to detect colored clothing amidst white or vice versa via camera vision, what if the clothing is hidden amidst the pile? Have to think through this capability. As with any camera vision product, tech is still nascent here and will need to be improved before a full scale launch can be done.

Problem 3- As mentioned in 2, if you have a mobile interface to your washer/dryer- you can get alerts and notifications right on your mobile device and do not need noisy alarms waking up your whole house and neighborhood.
I dont think this has any cons. This should be the easiest to implement as we now have the capability to lock doors through mobile as well. I havent done my research but perhaps this capability already exists for some washer/dryers.

Problem 4 – Folding clothes- I would like to have a robotics capability built in to the dryer to automatically take freshly dried clothes and fold them after the cycle. This can be an optional attachment to the unit. I remember seeing an innovative product like this on a youtube video once. Dont know if this is available yet for mass production. I would certainly like to explore it.
Pros – Its a great feature
Cons – Implementation might be hard depending on tech capabilities available

Problem 5 – Moving clothes from washer to dryer – I would like to have the same unit do the washing and the drying so that you dont have to remember to move clothes between them. This should be fairly doable but would require additional capabilities and horse power in the same mechanical/electrical unit.
Other option is to have a mechanical chute which uses electricity, gravitational mechanics to move the clothes from one unit to the other once washing is done. The user should be able to control on his/her mobile device which clothes they want to send to the dryer vs not.
Pros – By setting the right relative height between the washer and dryer and building the mechanical/electrical capability, this seems very doable
Cons – The mechanical chute solution could be very cumbersome and bulky and perhaps could damage clothes. Needs to go through R&D and testing.

Overall these solutions would be expensive except for the #3 solution. I would recommend partnering with detergent vendors who can have their advertising on the body of the washer/dryer which can have an LCD screen to show live ads. These vendors can also compete to have their detergent pre-filled in the detergent module of the washer (#1) – to help fund and reduce costs overall.
I am not going in to pricing and go to market strategy here as this is a design question.

answered by (149 points)
Hi Nabspm,
Thank you for the answer. It’s very detailed, structured, and easy to follow. The only feedback I would have is to say I would first ask what the goal of the design of the washer / dryer is. Do they have a particular objective in mind? (e.g. do they want to enable faster wash, increase lifetime of clothes, or something else) If they don’t have an objective in mind, I would select one particular objective and focus on features that help achieve that particular goal.
0 votes

Here is very simplified way of estimating drive-less car market in 2020. Market can be defined as total number of car sold in volume or it can be $$ value. I choose to estimate the volume. The value can also be estimated by multiplying the total number of cars sold in 2020 by average cost of vehicle

Ask clarifying question:

1. Are we estimating driver-less car purchases in US or worldwide - say the answer is US only

Make Equation:

Market for driver-less card = number of new car purchased in 2020 * market share of driver-less car

Number of new car purchased in 2020 = total number of cars in US/ car replacement cycle 

Total number of car in US  = total number of households in US * average car per household

Total number of households in US = total US population / number of person per household

Assumptions & Facts:

1. Replacement cycle for car is say 10 years, meaning after 10 years of usage the car needs to be replaced by new one

2. Number of person per household = 3

3. Average car per household = 2

4. It is expected that in 2018 Tesla will sell 200,000 cars which is less .5 % of overall market. Assuming the number of driver-less car sold doubles every year, than the market of driver-less car in 2019 be 1% and 2020 be 2%

5. US population = 300 million

Do the Math:

Total number of households in US = total US population / number of person per household

                                                        = 300 million/ 3 person per household

                                                        = 100 million household

Total number of car  = total number of households in US * average car per household

                                = 100 million * 2 cars per household

                                = 200 million cars

Number of new car purchased in 2020 = total number of cars in US/ car replacement cycle 

                                                               = 200 million cars/ 10 years

                                                               = 20 million new cars are purchased 

Market for driver-less card = number of new car purchased in 2020 * market share of driver-less car

                                           = 15 million new cars * 2%

                                           = 300,000

answered by (57 points)

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